High rates of head injury among homeless and low-income housed men: a retrospective cohort study
Bibliographic record
Abstract
OBJECTIVE: To examine the predictors and temporal patterns of head injury (HI) presentation in the emergency department among cohorts of homeless and low-income housed men. METHODS: Retrospective review and logistic regression of HIs found in emergency department records for three groups of men, those: (1) who were chronically homeless with drinking problems (CHDP) (n=50), (2) in the general homeless population (GH) (n=60) and (3) in low-income housing (LIH) (n=59). RESULTS: The proportion of individuals with non-minimal HIs documented in the previous year were 28%, 3% and 5% with annual rates of 0.47, 0.017 and 0.037 among the CHDP, GH and LIH groups (p<0.0001). In the multivariate model, independent associations with having an HI included: an HI in the previous year (OR 11.8, 95% CI 3.83 to 36.4), drug dependence (OR 3.67, 95% CI 1.11 to 12.13) and seizures (OR 3.50, 95% CI 1.13 to 10.90), while mood-disorders were protective. Homelessness had a crude risk increase of HI (OR 3.15, 95% CI 1.21 to 8.23) but was not significant in the multivariate model. Among those with HIs, chronic homelessness with drinking problems was associated with a higher rate of HI. With each successive HI, the time interval to another HI was 12 days shorter (p=0.0004). The chronic subdural haematoma incidence in the under-65-year-old CHDP group was 11 per 1000 (95% CI 2.8 to 45). CONCLUSIONS: Having an HI is better predicted by previous head injuries, drug dependence or a seizure disorder than a history of homelessness or alcohol dependence. HIs may become more frequent with time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".